Imaging plays a pivotal role in the management of patients with gynecological malignancies, contributing to diagnosis, the characterization of adnexal masses, evaluating lymph node metastasis, treatment planning, surgical guidance, and relapse monitoring. Recently, studies exploring the development of novel imaging tools and techniques, as well as new approaches combining imaging and treatment modalities, are creating new possibilities for improving the management of patients with gynecological malignancies.
In ovarian cancer, the application of microbubbles as a contrast agent has been explored for improving the detection of early-stage ovarian cancer and has demonstrated high sensitivity and specificity. Optical imaging is also being used extensively in the preclinical setting, as well as intraoperatively, where it can be utilized for tumor staging and debulking during cytoreductive surgery. Magnetic resonance imaging (MRI) is not often used in ovarian cancer diagnosis due to its high cost and limitations of availability, but it is often used in the assessment of complex ovarian masses following indeterminate ultrasound. Though MRI-based studies of ovarian cancer are limited, the integration of PET/MR scanners could enable the characterization of tumor molecular and metabolic features, subsequently paving the way for imaging and therapeutic guidance.
In cervical cancer, which has a high risk of recurrence, imaging plays a central role in pre-treatment evaluation. Recent research has been focusing on the identification of non-invasive biomarkers to enable more specific tumor characterization prior to therapy. Radiomics, a method by which data-characterization algorithms are used to extract features for cancer diagnosis or prediction from medical images, has been used to predict tumor stage, histological type, lymph node metastasis, relapse and survival.
In advanced gynecological malignancies, theranostic approaches combining the identification of suitable molecular targets, diagnostic imaging, and therapy have been shown to improve survival outcomes. Cancer cell-specific molecular targets are identified and imaging is then used to assess expression level and distribution, and subsequently to guide therapy and minimize toxicity. Another theranostic approach being explored is near-infrared photoimmunotherapy (NIR-PIT), which uses an antibody conjugated to a photoabsorber to target cancer cells and cause cellular damage when exposed to NIR light.
This collection aims to combine research investigating novel imaging tools and techniques in gynecological malignancies, which can improve early detection, staging, diagnosis, risk-stratification, surgical guidance, therapy, and treatment response monitoring, in order to improve survival outcomes for patients with gynecological malignancies.
Please note: manuscripts that are solely based on bioinformatics or computational analysis of public databases without validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Imaging plays a pivotal role in the management of patients with gynecological malignancies, contributing to diagnosis, the characterization of adnexal masses, evaluating lymph node metastasis, treatment planning, surgical guidance, and relapse monitoring. Recently, studies exploring the development of novel imaging tools and techniques, as well as new approaches combining imaging and treatment modalities, are creating new possibilities for improving the management of patients with gynecological malignancies.
In ovarian cancer, the application of microbubbles as a contrast agent has been explored for improving the detection of early-stage ovarian cancer and has demonstrated high sensitivity and specificity. Optical imaging is also being used extensively in the preclinical setting, as well as intraoperatively, where it can be utilized for tumor staging and debulking during cytoreductive surgery. Magnetic resonance imaging (MRI) is not often used in ovarian cancer diagnosis due to its high cost and limitations of availability, but it is often used in the assessment of complex ovarian masses following indeterminate ultrasound. Though MRI-based studies of ovarian cancer are limited, the integration of PET/MR scanners could enable the characterization of tumor molecular and metabolic features, subsequently paving the way for imaging and therapeutic guidance.
In cervical cancer, which has a high risk of recurrence, imaging plays a central role in pre-treatment evaluation. Recent research has been focusing on the identification of non-invasive biomarkers to enable more specific tumor characterization prior to therapy. Radiomics, a method by which data-characterization algorithms are used to extract features for cancer diagnosis or prediction from medical images, has been used to predict tumor stage, histological type, lymph node metastasis, relapse and survival.
In advanced gynecological malignancies, theranostic approaches combining the identification of suitable molecular targets, diagnostic imaging, and therapy have been shown to improve survival outcomes. Cancer cell-specific molecular targets are identified and imaging is then used to assess expression level and distribution, and subsequently to guide therapy and minimize toxicity. Another theranostic approach being explored is near-infrared photoimmunotherapy (NIR-PIT), which uses an antibody conjugated to a photoabsorber to target cancer cells and cause cellular damage when exposed to NIR light.
This collection aims to combine research investigating novel imaging tools and techniques in gynecological malignancies, which can improve early detection, staging, diagnosis, risk-stratification, surgical guidance, therapy, and treatment response monitoring, in order to improve survival outcomes for patients with gynecological malignancies.
Please note: manuscripts that are solely based on bioinformatics or computational analysis of public databases without validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
